LLMOps (LLM Bootcamp)

On this video, Josh offers a tour of the rising self-discipline of LLMOps: ideas and practices for steady enchancment of enormous language model-powered purposes.

– Evaluating and evaluating open supply and proprietary fashions– Workflows and instruments for iteration and immediate administration– Rules for making use of test-driven improvement to LLMs

Obtain slides and think about lecture notes: https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/llmops/

Intro and outro music made with Riffusion: https://github.com/riffusion/riffusion

Watch the remainder of the LLM Bootcamp movies right here: https://www.youtube.com/playlist?list=PL1T8fO7ArWleyIqOy37OVXsP4hFXymdOZ

00:00 Why LLMOps?01:55 Selecting your base LLM04:20 Proprietary LLMs09:15 Open-source LLMs14:45 Iteration and immediate administration22:35 Testing LLMs: Why and why is it laborious?28:15 Testing LLMs: What works?35:05 Analysis metrics for LLMs37:40 Deployment and monitoring44:35 Check-driven improvement for LLMs

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